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  • Amazon Research Award recipient
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  • The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning.
    July 6 - 11, 2026
    Seoul, South Korea
  • The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses.
    June 3 - 7, 2026
    Denver, Colorado
  • Amazon Research Day is an in-person event that connects Amazonians with academic research partners to advance breakthrough innovation by sharing research insights and exploring new collaboration opportunities. Designed as a highly curated, invite-only forum, the event features poster sessions, networking opportunities, and inspiring talks from both Amazon science leaders and prominent external researchers across a range of disciplines.
    April 30 - May 1, 2026
    Palo Alto, California
  • The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.
    April 23 - 27, 2026
    Rio de Janeiro, Brazil
  • The Web Conference (formerly known as the International World Wide Web Conference, abbreviated WWW) has been the premier annual forum for presenting and discussing advances in research, development, standards, and applications shaping the future of the Web.
    April 13 - 17, 2026
    Dubai, United Arab Emirates
  • Gradient orthogonalization is a simple strategy that shows great utility in speeding up gradient descent. The Muon optimizer (Jordan et al., 2024b) combines gradient orthogonalization with first-order momentum and achieves significant improvement in data efficiency over Adam/AdamW (Loshchilov & Hutter, 2019a) for language model training. However, when using model parallelism, gradient orthogonalization
US, WA, Seattle
This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scalable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.
US, WA, Seattle
WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale. We are looking for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials. You will develop new science-based forecasting methodologies and build scalable models to improve financial decision making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores. We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action. Key job responsibilities Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models Working with technical and non-technical stakeholders across every step of science project life cycle Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models Innovating by adapting new modeling techniques and procedures Presenting research results to our internal research community
IN, KA, Bengaluru
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Research Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Research Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.
US, WA, Bellevue
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems. The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.
US, WA, Bellevue
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems. The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.
US, WA, Bellevue
The Principal Applied Scientist will own the science mission for building next-generation proactive and autonomous agentic experiences across Alexa AI's Personalization, Autonomy and Proactive Intelligence organization. You will technically lead a team of applied scientists to harness state-of-the-art technologies in machine learning, natural language processing, LLM training and application, and agentic AI systems to advance the scientific frontiers of autonomous intelligence and proactive user assistance. The right candidate will be an inventor at heart, provide deep scientific leadership, establish compelling technical direction and vision, and drive ambitious research initiatives that push the boundaries of what's possible with AI agents. You will need to be adept at identifying promising research directions in agentic AI, developing novel autonomous agent solutions, and translating advanced AI research into production-ready agentic systems. You will need to be adept at influencing and collaborating with partner teams, launching AI-powered autonomous agents into production, and building team mechanisms that will foster innovation and execution in the rapidly evolving field of agentic AI. This role represents a unique opportunity to tackle fundamental challenges in how Alexa proactively understands user needs, autonomously takes actions on behalf of users, and delivers intelligent assistance through state-of-the-art agentic AI technologies. As a science leader in Alexa AI, you will shape the technical strategy for making Alexa a truly proactive and autonomous agent that anticipates user needs, takes intelligent actions, and provides seamless assistance without explicit prompting. Your team will be at the forefront of solving complex problems in agentic reasoning, multi-step task planning, autonomous decision-making, proactive intelligence, and context-aware action execution that will fundamentally transform how users interact with Alexa as an intelligent agent. The successful candidate will bring deep technical expertise in machine learning, natural language processing, and agentic AI systems, along with the leadership ability to guide talented scientists in pursuing ambitious research that advances the state of the art in autonomous agents, proactive intelligence, and AI-driven personalization. Experience with multi-agent systems, reinforcement learning, goal-oriented dialogue systems, and production-scale agentic architectures is highly valued. You will lead the development of breakthrough capabilities that enable Alexa to: 1) proactively anticipate user needs through advanced predictive modeling and contextual understanding; 2) autonomously execute complex multi-step tasks with minimal user intervention; 3) reason and plan intelligently across diverse user goals and environmental contexts; 4) learn and adapt continuously from user interactions to improve agentic behaviors; 5) coordinate actions seamlessly across multiple domains and services as a unified intelligent agent. This is a unique opportunity to define the future of conversational AI agents and build technology that will impact hundreds of millions of customers worldwide. Key job responsibilities Technical Leadership - Lead complex research and development projects - Partner closely with the T&C Product and Engineering leaders on the technical strategy and roadmap - Evaluate emerging technologies and methodologies - Make high-level architectural decisions Technical leadership and mentoring: - Mentor and develop technical talent - Set team project goals and metrics - Help with resource allocation and project prioritization from technical side Research & Development - Drive innovation in applied science areas - Translate research into practical business solutions - Author technical papers and patents - Collaborate with academic and industry partners About the team PAPI (Personalization Autonomy and Proactive Intelligence) aims to accelerate personalized and intuitive experiences across Amazon's customer touchpoints through automated, scalable, self-serve AI systems. We leverage customer, device, and ambient signals to deliver conversational, visual, and proactive experiences that delight customers, increase engagement, reduce defects, and enable natural interactions across Amazon touch points including Alexa, FireTV, and Mobile etc. Our systems offer personalized suggestions, comprehend customer inputs, learn from interactions, and propose appropriate actions to serve millions of customers globally.
US, CA, San Francisco
AWS is one of Amazon’s largest and fastest growing businesses, serving millions of customers in more than 190 countries. We use cloud computing to reshape the way global enterprises use information technology. We are looking for entrepreneurial, analytical, creative, flexible leaders to help us redefine the information technology industry. If you want to join a fast-paced, innovative team that is making history, this is the place for you. AWS Central Economics & Science (ACES) drives best practices for objectively applying economics and science in decision making across AWS. The team collaborates with AWS science and business teams to identify, frame, and analyze complex and ambiguous problems of the highest priority. Through data-driven insights and modeling, ACES supports strategic decision-making across the AWS global organization, including sales operations and business performance optimization. The ACES Sales Channels team is hiring an Applied Scientist (Senior or below) to advance our mission of providing rigorous, causal-inference-driven recommendations for AWS sales optimization. This role will focus on building ML systems with a causal modeling foundation, designing seller incentive mechanisms, and developing intervention strategies across the entire sales motion. Key job responsibilities • Causal ML System Development: Build and deploy machine learning models that emphasize causal inference, ensuring recommendations are grounded in valid interventions • Incentive Design: Define and model incentives that drive desirable behaviors across AWS sales channels, partner programs, and reseller ecosystems • Stakeholder Collaboration: Work with business stakeholders to understand requirements, validate approaches, and ensure practical applicability of scientific solutions • Scientific Rigor: Promote findings at internal conferences and contribute to the team's reputation for methodological excellence A day in the life The ACES Sales Channels team works on understanding and optimizing AWS's sales channels, both direct (generalist and specialist sellers) and indirect (partners and Marketplace). Our work falls into three core areas: developing rigorous causal measurement and modeling frameworks using cutting-edge economics and statistical methods; designing programs and incentives to improve customer and business outcomes; and building ML-based recommendation systems for sellers, partners, and other AWS stakeholders. About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.
US, WA, Seattle
Amazon has co-founded and signed The Climate Pledge, a commitment to reach net zero carbon by 2040. As a team, we leverage GenAI, sensors, smart home devices, cloud services, material science, and Alexa to build products that have a meaningful impact for customers and the climate. In alignment with this bold corporate goal, the Amazon Devices & Services organization is looking for a passionate, talented, and inventive Senior Applied Scientist to help build revolutionary products with potential for major societal impact. Great candidates for this position will have expertise in the areas of agentic AI applications, deep learning, time series analysis, LLMs, and multimodal systems. This includes experience designing autonomous AI agents that can reason, plan, and execute multi-step tasks, building tool-augmented LLM systems with access to external APIs and data sources, implementing multi-agent orchestration, and developing RAG architectures that combine LLMs with domain-specific knowledge bases. You will strive for simplicity and creativity, demonstrating high judgment backed by statistical proof. Key job responsibilities As a Senior Applied Scientist on the Energy Science team, you'll design and deploy agentic AI systems that autonomously analyze data, plan solutions, and execute recommendations. You'll build multi-agent architectures where specialized AI agents coordinate to solve complex optimization problems, and develop tool-augmented LLM applications that integrate with external data sources and APIs to deliver context-aware insights. Your work involves creating multimodal AI systems that synthesize diverse data streams, while implementing RAG pipelines that ground large language models in domain-specific knowledge bases. You'll apply advanced machine learning and deep learning techniques to time series analysis, forecasting, and pattern recognition. Beyond technical innovation, you'll drive end-to-end product development from research through production deployment, collaborating with cross-functional teams to translate AI capabilities into customer experiences. You'll establish rigorous experimentation frameworks to validate model performance and measure business impact, building AI-driven products with potential for major societal impact.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Research Scientist, you will work with a unique and gifted team developing exciting products for consumers and collaborate with cross-functional teams. Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the intersection of both academic and applied research in this product area, you have the opportunity to work together with some of the most talented scientists, engineers, and product managers. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
IN, KA, Bengaluru
Amazon Health Services (One Medical) About Us: At Health AI, we're revolutionizing healthcare delivery through innovative AI-enabled solutions. As part of Amazon Health Services and One Medical, we're on a mission to make quality healthcare more accessible while improving patient outcomes. Our work directly impacts millions of lives by empowering patients and enabling healthcare providers to deliver more meaningful care. Role Overview: We're seeking an Applied Scientist to join our dynamic team in building state of the art AI/ML solutions for healthcare. This role offers a unique opportunity to work at the intersection of artificial intelligence and healthcare, developing solutions that will shape the future of medical services delivery. Key job responsibilities • Lead end-to-end development of AI/ML solutions for Amazon Health organization, including Amazon Pharmacy and One Medical • Research, design, and implement state-of-the-art machine learning models, with a focus on Large Language Models (LLMs) and Visual Language Models (VLMs) • Optimize and fine-tune models for production deployment, including model distillation for improved latency • Drive scientific innovation while maintaining a strong focus on practical business outcomes • Collaborate with cross-functional teams to translate complex technical solutions into tangible customer benefits • Contribute to the broader Amazon Health scientific community and help shape our technical roadmap